生命科學領域人工智慧市場－全球產業規模、佔有率、趨勢、機會、預測：按交付方式、部署方式、應用領域、地區和競爭格局分類，2021-2031年

全球生命科學領域的人工智慧市場預計將從 2025 年的 142.1 億美元大幅成長至 2031 年的 336.1 億美元，複合年成長率為 15.43%。

在這個領域，我們整合了機器學習、自然語言處理和先進的計算演算法等人工智慧技術，以加速藥物發現、改進臨床試驗調查方法並提高診斷準確性。

市場成長主要受複雜生物醫學數據激增的驅動。為了有效處理這些數據，亟需自動化分析解決方案，以降低藥物研發過程中固有的高成本和冗長流程。然而，一個重大挑戰依然存在：技術專家的短缺阻礙了人工智慧解決方案的無縫整合和規模化應用。企業難以找到同時精通生物科學和數據工程的專家；根據皮斯托亞聯盟 (Pistoia Alliance) 發布的 2025 年報告，34% 的行業相關人員認為缺乏熟練人員是實驗室採用人工智慧的主要障礙。因此，計算工具的全部潛力未能充分發揮，限制了市場的整體擴張。

市場促進因素

推動市場成長的根本動力在於迫切需要擺脫傳統的、資本密集的製藥模式，加速藥物發現並降低巨額研發成本。人工智慧演算法正被擴大用於預測分子間相互作用和篩選先導化合物，從而大幅縮短通常需要數年的臨床前試驗階段。這種效率的提升吸引了大型製藥企業的大量投資，他們希望將檢驗的人工智慧平台整合到自身的研發流程中。例如，根據Labiotech.eu於2025年10月報道，Astra Zeneca與石藥集團（CSPC Pharmaceuticals）達成合作，其中包括1.1億美元的首付和高達36億美元的里程碑付款。

同時，生成式人工智慧和深度學習模型的快​​速發展正在改變生命科學產業的技術基礎。這些模型能夠分析海量多組體學資料集並設計新型蛋白質結構，對先進的運算能力產生了巨大的需求。這一趨勢體現在技術提供者的快速擴張。例如，英偉達資料中心部門在2025年11月創下了512億美元的營收紀錄，年增66%。正如該公司2026年第三季報告中所述，這主要得益於生物和工業應用領域對基礎模型的採用。這種技術的成熟也吸引了大量創業投資湧入專業公司。根據Tech Funding News在2025年12月報道，Isomorphic Labs成功資金籌措了6億美元，用於推進人工智慧驅動的藥物發現，這印證了市場對深度學習在治療方法創新領域潛力的信心。

市場挑戰

缺乏專業技術人才正嚴重阻礙全球生命科學人工智慧市場的發展，主要表現在難以將先導計畫轉化為全面商業化應用。這項挑戰源自於對具備「雙語」技能的專家的需求；也就是說，專家既需要深厚的複雜生物科學知識，也需要精通數據工程。缺乏這種綜合能力，企業將面臨營運障礙，難以有效檢驗計算結果並將其轉化為可執行的研發成果，導致產品開發進程顯著延誤。

熟練人才短缺迫使企業將資源重新分配到內部培訓和技能發展計畫中，而非專注於近期的市場擴張。這種內部知識缺口巨大。皮斯托亞聯盟在2025年報告中發現，45%的業界專業人士特別希望參加人工智慧和機器學習的培訓課程，以彌補自身技能差距。這種對基礎培訓的強勁需求表明，目前相當一部分員工尚未做好利用先進人工智慧工具的準備。因此，市場成長正在放緩，因為企業必須先建立必要的人力資本，才能充分利用自動化分析能力。

市場趨勢

一個關鍵趨勢是擴大採用自主人工智慧代理來簡化複雜工作流程的自動化。這標誌著從靜態的、指令驅動的工具轉變為能夠實現多階段目標的自主系統。這些代理自主運行，無需持續的人工干預即可管理監管合規性、檢驗科學數據並創建可提交的文檔，從而顯著減少行政瓶頸。這種能力對於最大限度地減少通常與合規性和臨床報告相關的繁瑣的人工工作至關重要。 Deep Intelligent Pharma 於 2025 年 5 月發布的新聞稿重點介紹了其平台利用多代理人工智慧叢集進行自動化統計推斷和檢驗，從而將創建臨床和監管文件所需的時間縮短 90% 以上的能力，並提供了相關證據。

同時，生成式人工智慧在新型蛋白質和抗體設計中的應用，正將此領域從簡單的篩檢現有庫轉變為主動設計具有特定治療特性的新型生物實體。透過利用基於海量生物資料集訓練的基礎模型，研究人員現在可以從零開始設計蛋白質，甚至在物理合成之前最佳化其可開發性和結合親和性。這種從純粹的發現到工程主導方法的轉變，正在吸引大量投資，並凸顯生成式生物學的商業性潛力。例如，根據《科技時報》（Tech Times）2025年12月的一篇報導，Chai Discovery公司獲得了1.3億美元的B輪資金籌措，用於推動這些生成式能力的發展，並將分子生物學重新定義為一個工程領域。

目錄

第1章概述

第2章：調查方法

第3章執行摘要

第4章：客戶心聲

第5章：生命科學領域全球人工智慧市場展望

• 市場規模及預測
  • 按金額
• 市佔率及預測
  • 依交付方式（軟體、硬體、服務）
  • 依部署方式（本機部署、雲端部署）
  • 應用領域（醫療診斷、藥物研發、精準醫療與個人化醫療、生物技術、臨床試驗、專利監測）
  • 按地區
  • 按公司（2025 年）
• 市場地圖

第6章：北美生命科學領域人工智慧市場展望

• 市場規模及預測
• 市佔率及預測
• 北美洲：國別分析
  • 美國
  • 加拿大
  • 墨西哥

第7章：歐洲生命科學領域人工智慧市場展望

• 市場規模及預測
• 市佔率及預測
• 歐洲：國別分析
  • 德國
  • 法國
  • 英國
  • 義大利
  • 西班牙

第8章：亞太地區生命科學領域人工智慧市場展望

• 市場規模及預測
• 市佔率及預測
• 亞太地區：國別分析
  • 中國
  • 印度
  • 日本
  • 韓國
  • 澳洲

第9章：中東和非洲生命科學領域人工智慧市場展望

• 市場規模及預測
• 市佔率及預測
• 中東與非洲：國別分析
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國
  • 南非

第10章：南美洲生命科學領域人工智慧市場展望

• 市場規模及預測
• 市佔率及預測
• 南美洲：國別分析
  • 巴西
  • 哥倫比亞
  • 阿根廷

第11章 市場動態

• 促進因素
• 任務

第12章 市場趨勢與發展

• 併購
• 產品發布
• 近期趨勢

第13章：全球生命科學領域人工智慧市場：SWOT分析

第14章：波特五力分析

• 產業競爭
• 新進入者的潛力
• 供應商的議價能力
• 顧客權力
• 替代品的威脅

第15章 競爭格局

• IBM Corporation
• Atomwise Inc.
• Nuance Communications, Inc.
• NuMedii, Inc.
• AiCure LLC
• Apixio Holdings, LLC
• Insilico Medicine
• Enlitic, Inc.
• Sensely, Inc.
• SINEQUA Group

第16章 策略建議

第17章：關於研究公司及免責聲明

The global market for AI in Life Science is projected to expand significantly, increasing from USD 14.21 billion in 2025 to USD 33.61 billion by 2031, demonstrating a compound annual growth rate (CAGR) of 15.43%. This sector integrates artificial intelligence technologies, including machine learning, natural language processing, and advanced computational algorithms, to expedite drug discovery, refine clinical trial methodologies, and improve diagnostic precision.

The market's growth is largely fueled by the surging volume of intricate biomedical data, which demands automated analytical solutions for effective processing, alongside the critical need to mitigate the high costs and protracted timelines inherent in pharmaceutical development. However, a notable challenge persists in the form of a shortage of technical experts, impeding the seamless integration and scaling of AI solutions. Businesses struggle to find professionals skilled in both biological sciences and data engineering, with the Pistoia Alliance reporting in 2025 that 34% of industry participants identified a lack of skilled personnel as a primary obstacle to AI adoption in laboratory settings, consequently limiting the full potential of computational tools and overall market expansion.

Market Driver

A fundamental driver for market growth is the pressing need to accelerate drug discovery and reduce substantial research and development expenses, aiming to move beyond the conventional, capital-intensive pharmaceutical paradigm. AI algorithms are increasingly utilized to forecast molecular interactions and refine lead candidates, significantly cutting down the multi-year preclinical testing phases. This enhanced efficiency is attracting substantial financial investments from leading pharmaceutical firms looking to incorporate validated AI platforms into their development processes, exemplified by AstraZeneca's partnership with CSPC Pharmaceuticals, which included a $110 million upfront payment and up to $3.6 billion in potential milestone payments, as reported by Labiotech.eu in October 2025.

Simultaneously, swift progress in generative AI and deep learning models is transforming the technological foundation of the life sciences industry. These models' capacity to analyze extensive multi-omics datasets and engineer novel protein structures has generated considerable demand for advanced computing power. This trend is reflected in the rapid expansion of technology providers; for instance, NVIDIA's Data Center revenue surged to a record $51.2 billion in November 2025, a 66% increase largely attributable to the deployment of foundation models for biological and industrial uses, as detailed in their Q3 Fiscal 2026 report. Such technological maturity is also drawing significant venture capital into specialized companies, with Isomorphic Labs securing $600 million to advance its AI-driven drug design, underscoring the market's conviction in deep learning's potential for therapeutic innovations, according to Tech Funding News in December 2025.

Market Challenge

The shortage of specialized technical expertise significantly impedes the growth of the Global AI in Life Science Market, primarily by hindering the progression from pilot projects to comprehensive commercial implementation. This challenge arises from the need for professionals with a "bilingual" skillset, meaning individuals must possess both profound knowledge in intricate biological sciences and advanced competency in data engineering. Without this combined capability, organizations encounter operational obstacles, preventing the effective validation of computational insights or their translation into actionable R&D results, thereby causing substantial delays in product development.

This dearth of skilled personnel compels companies to reallocate resources towards internal training and upskilling initiatives, rather than focusing on immediate market expansion. The extent of this internal knowledge gap is considerable; the Pistoia Alliance reported in 2025 that 45% of industry professionals specifically sought educational courses in AI and machine learning to address their skill deficiencies. This strong demand for fundamental training suggests that a significant segment of the current workforce is not yet equipped to utilize advanced AI tools. As a result, the market's growth momentum is slowed, as businesses must first establish essential human capital before they can fully exploit automated analytical capabilities.

Market Trends

A significant trend involves the increasing adoption of autonomous AI agents for streamlining complex workflow automation, marking a shift from static, prompt-driven tools to self-governing systems capable of fulfilling multi-step objectives. These agents operate independently, managing regulatory compliance, validating scientific data, and producing submission-ready documentation without continuous human intervention, thereby substantially alleviating administrative bottlenecks. This functionality is crucial for minimizing the manual effort typically associated with compliance and clinical reporting, as evidenced by Deep Intelligent Pharma's May 2025 press release, which highlighted their platform's ability to reduce clinical and regulatory documentation time by over 90% using multi-agent AI swarms for automated statistical reasoning and validation.

Simultaneously, the application of generative AI for de novo protein and antibody design is transforming the sector from merely screening existing libraries to actively engineering novel biological entities possessing specific therapeutic characteristics. Utilizing foundation models trained on extensive biological datasets, researchers can now design proteins from the ground up, optimizing them for developability and binding affinity even before physical synthesis. This shift from pure discovery to an engineering-driven approach is attracting considerable investment, confirming the commercial potential of generative biology. For example, Chai Discovery secured a $130 million Series B funding round to advance these generative capabilities and redefine molecular biology as an engineering discipline, according to a December 2025 US Tech Times article.

Key Market Players

• IBM Corporation
• Atomwise Inc.
• Nuance Communications, Inc.
• NuMedii, Inc.
• AiCure LLC
• Apixio Holdings, LLC
• Insilico Medicine
• Enlitic, Inc.
• Sensely, Inc.
• SINEQUA Group

Report Scope

In this report, the Global AI in Life Science Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

AI in Life Science Market, By Offering

• Software
• Hardware
• Services

AI in Life Science Market, By Deployment

• On-Premises
• Cloud

AI in Life Science Market, By Application

• Medical Diagnosis
• Drug Discovery
• Precision & Personalized Medicine
• Biotechnology
• Clinical Trials
• Patent Monitoring

AI in Life Science Market, By Region

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
• South America
  • Brazil
  • Argentina
  • Colombia
• Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global AI in Life Science Market.

Available Customizations:

Global AI in Life Science Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global AI in Life Science Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Offering (Software, Hardware, Services)
  • 5.2.2. By Deployment (On-Premises, Cloud)
  • 5.2.3. By Application (Medical Diagnosis, Drug Discovery, Precision & Personalized Medicine, Biotechnology, Clinical Trials, Patent Monitoring)
  • 5.2.4. By Region
  • 5.2.5. By Company (2025)
• 5.3. Market Map

6. North America AI in Life Science Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Offering
  • 6.2.2. By Deployment
  • 6.2.3. By Application
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States AI in Life Science Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Offering
      • 6.3.1.2.2. By Deployment
      • 6.3.1.2.3. By Application
  • 6.3.2. Canada AI in Life Science Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Offering
      • 6.3.2.2.2. By Deployment
      • 6.3.2.2.3. By Application
  • 6.3.3. Mexico AI in Life Science Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Offering
      • 6.3.3.2.2. By Deployment
      • 6.3.3.2.3. By Application

7. Europe AI in Life Science Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Offering
  • 7.2.2. By Deployment
  • 7.2.3. By Application
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany AI in Life Science Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Offering
      • 7.3.1.2.2. By Deployment
      • 7.3.1.2.3. By Application
  • 7.3.2. France AI in Life Science Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Offering
      • 7.3.2.2.2. By Deployment
      • 7.3.2.2.3. By Application
  • 7.3.3. United Kingdom AI in Life Science Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Offering
      • 7.3.3.2.2. By Deployment
      • 7.3.3.2.3. By Application
  • 7.3.4. Italy AI in Life Science Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Offering
      • 7.3.4.2.2. By Deployment
      • 7.3.4.2.3. By Application
  • 7.3.5. Spain AI in Life Science Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Offering
      • 7.3.5.2.2. By Deployment
      • 7.3.5.2.3. By Application

8. Asia Pacific AI in Life Science Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Offering
  • 8.2.2. By Deployment
  • 8.2.3. By Application
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China AI in Life Science Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Offering
      • 8.3.1.2.2. By Deployment
      • 8.3.1.2.3. By Application
  • 8.3.2. India AI in Life Science Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Offering
      • 8.3.2.2.2. By Deployment
      • 8.3.2.2.3. By Application
  • 8.3.3. Japan AI in Life Science Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Offering
      • 8.3.3.2.2. By Deployment
      • 8.3.3.2.3. By Application
  • 8.3.4. South Korea AI in Life Science Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Offering
      • 8.3.4.2.2. By Deployment
      • 8.3.4.2.3. By Application
  • 8.3.5. Australia AI in Life Science Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Offering
      • 8.3.5.2.2. By Deployment
      • 8.3.5.2.3. By Application

9. Middle East & Africa AI in Life Science Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Offering
  • 9.2.2. By Deployment
  • 9.2.3. By Application
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia AI in Life Science Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Offering
      • 9.3.1.2.2. By Deployment
      • 9.3.1.2.3. By Application
  • 9.3.2. UAE AI in Life Science Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Offering
      • 9.3.2.2.2. By Deployment
      • 9.3.2.2.3. By Application
  • 9.3.3. South Africa AI in Life Science Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Offering
      • 9.3.3.2.2. By Deployment
      • 9.3.3.2.3. By Application

10. South America AI in Life Science Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Offering
  • 10.2.2. By Deployment
  • 10.2.3. By Application
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil AI in Life Science Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Offering
      • 10.3.1.2.2. By Deployment
      • 10.3.1.2.3. By Application
  • 10.3.2. Colombia AI in Life Science Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Offering
      • 10.3.2.2.2. By Deployment
      • 10.3.2.2.3. By Application
  • 10.3.3. Argentina AI in Life Science Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Offering
      • 10.3.3.2.2. By Deployment
      • 10.3.3.2.3. By Application

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends & Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Global AI in Life Science Market: SWOT Analysis

14. Porter's Five Forces Analysis

• 14.1. Competition in the Industry
• 14.2. Potential of New Entrants
• 14.3. Power of Suppliers
• 14.4. Power of Customers
• 14.5. Threat of Substitute Products

15. Competitive Landscape

• 15.1. IBM Corporation
  • 15.1.1. Business Overview
  • 15.1.2. Products & Services
  • 15.1.3. Recent Developments
  • 15.1.4. Key Personnel
  • 15.1.5. SWOT Analysis
• 15.2. Atomwise Inc.
• 15.3. Nuance Communications, Inc.
• 15.4. NuMedii, Inc.
• 15.5. AiCure LLC
• 15.6. Apixio Holdings, LLC
• 15.7. Insilico Medicine
• 15.8. Enlitic, Inc.
• 15.9. Sensely, Inc.
• 15.10. SINEQUA Group

16. Strategic Recommendations

17. About Us & Disclaimer